如果用户改变键盘或他的心情在击键动态中发生变化，我需要一个解决方案吗？
我的毕业项目是关于用户的击键动态认证，在识别阶段我遇到了一些问题（用户改变键盘，他们发生的干扰改变了他们的书写特征）。如果他们的算法可以解决这个问题或在系统训练阶段提出任何想法。
谢谢 ：）
my graduation project is about keystroke dynamic authentication for user and i have some problems (the users change their keyboard , Distractions happened to them change their writing characteristics) in the identification phase . if their is an algorithm over come this problems or any idea to be made in training phase for the system .
thanks :)
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来自 Wikipedia：击键动力学是更大类别的生物识别技术（称为行为生物识别技术）的一部分；它们的模式本质上是统计性的。人们普遍认为，行为生物识别技术不如用于身份验证的物理生物识别技术（例如指纹、视网膜扫描或 DNA）可靠。这里的现实是行为生物识别使用置信度测量而不是传统的通过/失败测量。因此，传统的错误接受率（FAR）和错误拒绝率（FRR）基准不再具有线性关系。
或者，用简单的英语来说，您将必须有一个漫长的识别阶段，以便您可以确定统计模式，而不是任何单独的模式。
From Wikipedia: Keystroke dynamics is part of a larger class of biometrics known as behavioral biometrics; their patterns are statistical in nature. It is a commonly held belief that behavioral biometrics are not as reliable as physical biometrics used for authentication such as fingerprints or retinal scans or DNA. The reality here is that behavioral biometrics use a confidence measurement instead of the traditional pass/fail measurements. As such, the traditional benchmarks of False Acceptance Rate (FAR) and False Rejection Rates (FRR) no longer have linear relationships.
Or, in plain English, you're going to have to have a long identification phase so that you can determine the statistical patterns, rather than any individual pattern.